#   Licensed to the Apache Software Foundation (ASF) under one
#   or more contributor license agreements.  See the NOTICE file
#   distributed with this work for additional information
#   regarding copyright ownership.  The ASF licenses this file
#   to you under the Apache License, Version 2.0 (the
#   "License"); you may not use this file except in compliance
#   with the License.  You may obtain a copy of the License at
#
#       http://www.apache.org/licenses/LICENSE-2.0
#
#   Unless required by applicable law or agreed to in writing, software
#   distributed under the License is distributed on an "AS IS" BASIS,
#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#   See the License for the specific language governing permissions and
#   limitations under the License.

#   beam-playground:
#     name: CoreTransformsSolution1
#     description: Core Transforms first motivating solution.
#     multifile: false
#     context_line: 57
#     categories:
#       - Quickstart
#     complexity: BASIC
#     tags:
#       - hellobeam

import apache_beam as beam

# Output PCollection
class Output(beam.PTransform):
    class _OutputFn(beam.DoFn):
        def __init__(self, prefix=''):
            super().__init__()
            self.prefix = prefix

        def process(self, element):
            print(self.prefix+str(element))

    def __init__(self, label=None,prefix=''):
        super().__init__(label)
        self.prefix = prefix

    def expand(self, input):
        input | beam.ParDo(self._OutputFn(self.prefix))


def partition_fn(word, num_partitions):
    if word.upper()==word:
        return 0
    if word[0].isupper():
        return 1
    else:
        return 2


with beam.Pipeline() as p:
  parts = p | 'Log lines' >> beam.io.ReadFromText('gs://apache-beam-samples/shakespeare/kinglear.txt') \
            | beam.combiners.Sample.FixedSizeGlobally(100) \
            | beam.FlatMap(lambda line: line) \
            | beam.FlatMap(lambda sentence: sentence.split()) \
            | beam.Partition(partition_fn, 3)

  allLetterUpperCase = parts[0] | 'All upper' >> beam.combiners.Count.PerElement() | beam.Map(lambda key: (key[0].lower(),key[1]))
  firstLetterUpperCase = parts[1] | 'First upper' >> beam.combiners.Count.PerElement() | beam.Map(lambda key: (key[0].lower(),key[1]))
  allLetterLowerCase = parts[2] | 'Lower' >> beam.combiners.Count.PerElement()

  flattenPCollection = (allLetterUpperCase, firstLetterUpperCase, allLetterLowerCase) \
            | beam.Flatten() \
            | beam.GroupByKey() \
            | Output()